Pfizer, in medicine by leaps and bounds of artificial intelligence for diagnosis and treatment

What role for artificial intelligence (Ai) in precision medicine? What are the possible fields of clinical application in this moment in which medicine is also at the center of a ‘digital revolution’? These are just some of the questions that were answered during ConnAction, the series of virtual events dedicated to doctors on issues related to Digital Health, promoted by Pfizer Healthcare Hub. Meetings, just concluded, which highlighted the giant steps made by AI in medicine. Specialists and innovators from the world of Healthech discussed the issues that in this moment of health emergency have highlighted the role of digitalization in medical practice and governance from diagnosis to treatment such as, for example, in the application of AI in diagnostics. by images (medical imaging), the central theme of the virtual meeting. “In the definition of artificial intelligence in medicine, we think of the set of applications that refer to human intelligence applied to machines to reduce, for example, the margin of human error”, explained Luca Maria Sconfienza, Director of the Diagnostic Radiology Operating Unit. and interventional, Ircss Policlinico San Donato (Milan). “In radiology, for example, it means – he added – better ability to read images, but also prognostic contributions, or a stratification of risk starting from the patient’s medical records. And let’s not forget the theme of the use of big data and privacy ‘nodes’ “. In recent years – a note reads – artificial intelligence has made great strides, as evidenced by the approval by the American FDA of a series of algorithms useful for diagnosis in the medical field. But the future goal is that AI can reliably outperform human performance. “A fundamental opportunity not only in radiology, but for the entire medical field – adds Sconfienza – I imagine a future in which the AI ​​will not replace the radiologist or the doctor, as has also been foreseen by someone, but it will be an important resource for health professionals who will know how to use it. “A future that seems close at hand is the one presented by the four startups that have distinguished themselves for innovation and digital solutions in remote patient management. One is Volv global, a Swiss startup whose mission is to accelerate the progress of science, reduce the cost of healthcare, improve economic output and the well-being of all. Thanks to their tools, it helps diagnose rare or difficult to diagnose diseases. Volv’s data science team specializes in using real-world data, both structured and unstructured, to build robust predictive models to improve patient outcomes. The second is Kaiku health, a Finnish company that has created a platform for digital health interventions. Provides monitoring of patient reported results and intelligent monitoring of their symptoms. Using Kaiku Health helps cancer clinics deliver optimized care through timely symptom management and better workflow. Kaiku was acquired by Elekta in 2020. Then there is Hynnova, a startup that applies the best data science techniques to the Helthcare sector. It was launched within the Eit Digital Innovation Factory and has developed two products that use machine learning to dynamically optimize the use of healthcare spaces and resources. They are currently used to optimize home care activities and Covid-19 vaccination campaigns in the northern area of ​​the Metropolitan City of Turin. And again: Image biopsy lab, an Austrian startup whose mission is to improve the quality of life of over a billion patients suffering from muscular and skeletal diseases by providing AI-guided solutions. Their tools increase the workflow of radiology tools, enabling early diagnosis and prevention of musculoskeletal diseases. “Artificial intelligence is a fundamental ingredient for digital transformation, and an essential tool for the new medicine, which will take therapy ‘beyond the pill'”, emphasizes Päivi Kerkola, Country Manager of Pfizer Italy. “A revolution concludes – that it cannot fail to start from the critical issues, from the ‘pain points’, of the patients’ path with the aim of offering a truly personalized therapy. Artificial intelligence is therefore essential for the new precision medicine: we are already thinking about the contribution of algorithms in predicting the patient’s reactions to therapy “.